AI at work: Insights from 20 leading technology companies

Artificial intelligence (AI) is no longer a future concern. It is already reshaping how people work, learn and grow. Three years after the launch of ChatGPT, companies across sectors are moving beyond small pilots and are starting to embed AI into their daily operations. An aggregated outlook from the World Economic Forum’s Communications and Technology Industry Strategy Officers community captures how this shift is unfolding inside more than 20 leading technology firms and their clients.

The community paper AI at Work: From Productivity Hacks to Organizational Transformation shows meaningful progress, but also many challenges. AI is raising productivity in specific workflows, improving client interactions and expanding opportunities for workers. At the same time, it is altering job tiers, pressuring mid-level roles, undermining trust, and forcing leaders to rethink the structure of the modern workplace.

One insight that emerges from the paper is that AI already excels at performing complex tasks. AI is handling contract reviews, complex financial checks and design tasks. One company used AI to analyse three months of tax data and 150 pages of regulation, which revealed $120 million in savings and reduced a key filing cycle from weeks to three days. Another firm shortened a 30-minute lab-ordering process to seconds and saved 30,000 hours per year.

However, these benefits appear only when leaders redesign workflows and prepare teams to leverage AI to reprioritize their outputs. This is in line with the findings of a recent MIT paper, which suggests that 95% of generative AI projects do not generate positive ROI when they stay limited to isolated experiments. Companies that succeed invest early in data quality, governance and workforce readiness through training and proactive integration into workflows.

As Nathan Jokel, Cisco’s senior vice-president of corporate strategy and alliances, points out, “Across multiple industries, we already see gains as AI enables individual employees to complete tasks more quickly and accurately. However, the bulk of the opportunity is yet ahead of us. The greatest transformation will come as organizations redesign workflows from the ground up around AI and invest in advanced AI skills for their teams.”

Public debate often focuses on AI affecting entry-level jobs, but the experiences of the community indicate mid-level positions may actually face greater disruption.

Yes, entry-level employees have fewer routine tasks, but many companies are speeding up early-career development to compensate. New hires now join client conversations and problem-solving sessions sooner, supported by AI copilots and knowledge assistants. AI creates opportunities for earlier skill development in areas that were previously associated with mid- to senior level employees.

As a result, it is mid-career professionals who may face growing pressures as AI enables entry-level staff to advance quickly and specialists to focus on complex tasks, potentially reducing the need for middle management. While evidence remains anecdotal, AI could impact mid-level roles more than junior positions, challenging common assumptions.

Hala Zeine, senior vice-president and chief strategy officer at ServiceNow, points out that these changes are already happening and will continue to accelerate. “Looking ahead, we will work with AI to support us in decision-making, take on repetitive but necessary tasks, and allow us to focus on meaningful work. It is inevitable – we will see org charts incorporate AI agents as formal team members alongside humans, assigning them defined responsibilities and performance metrics, which signals a clear shift towards hybrid human-AI teams.”

Executives also report that AI is reducing burnout, speeding up learning and making work more engaging as it frees up space for strategic thinking. Workers are spending less time on repetitive tasks and more time on problem-solving, client discussions and experimentation. Some firms use AI tools to support communication training or personalized career guidance.

Most companies do not measure these benefits, but the paper suggests that cultural gains may be among the most important long-term outcomes of AI adoption.

Trust remains the biggest barrier to scaling AI. Employees hesitate to rely on AI when the reasoning behind outputs is unclear or when accountability for mistakes is undefined.

Leaders worry about privacy, bias, accuracy and misinformation, especially in certain industries, as Pegasystems’ vice-president of strategy and transformation, Steve Rudolph, highlights: “AI serves different purposes at design time versus run time. At design time, AI drives innovation and creativity – variability in outputs is acceptable as we explore possibilities. At run time in operational environments, especially in regulated industries like banking, healthcare and insurance, we need predictability and traceability. AI must be orchestrated to ensure consistent, auditable outcomes rather than operating as an unpredictable black box.”

Successful companies invest in governance early. This includes explainable AI, clear review processes for AI agents and continuous testing or oversight. Without it, even the most promising tools risk becoming untrusted black boxes.

AI adoption is uneven across regions and company sizes. Large enterprises are driving early development, while smaller firms and emerging markets are producing inventive, context-specific applications. Many are leapfrogging outdated systems by using AI-first tools delivered through mobile infrastructure.

At the same time, a central challenge is providing workers with inclusive and equitable economic opportunities in an AI-driven landscape, which requires overcoming barriers to technology access, adapting skills development for evolving job requirements, and supporting career transitions for those without traditional backgrounds.

The Communications and Technology community at the World Economic Forum recognizes its responsibility in helping drive this transition. At the World Economic Forum Annual Meeting 2026, industry leaders from 25 companies will formalize the “Commitment to Creating Economic Opportunities for All in the Intelligent Age.” This pledge, which will collectively impact more than 120 million people by 2030, will include three pillars:

1. Access

Provide workers with access to AI tools at low or no cost, with attention to language, culture and socioeconomic barriers.

2. Skills

Support workers everywhere with digital and human skills that help them succeed in AI-augmented roles.

3. Job pathways

Create practical routes into AI-native jobs through apprenticeships, skills-based hiring and community outreach.

Shaping an inclusive future is not a task for the technology sector alone. As Ajay Bhaskar, chief strategy and transformation officer at Wipro, notes, “The tech industry does not just innovate gadgets or solutions; it shapes the future direction of economies and societies. As AI becomes deeply embedded in our lives, it is imperative for the sector to be proactive and lead the way in developing the broader workforce in the context of a Human+AI future.”

Achieving this calls for ongoing dialogue and partnership between business, government, academia and wider society. The transformation of work is already underway, and our collective actions – rooted in leadership, lifelong learning and responsible innovation – will ultimately decide whether AI serves as a force for shared prosperity or deepens divisions.

If you’re inspired to play your part in building a future where everyone benefits from AI, get involved with the Reskilling Revolution and help turn this vision into reality.